Application of U-Net for the Recognition of Regional Features in Geophysical Inversion Results
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DOI: 10.1109/tgrs.2021.3138790
Abstract: Engineering geophysical prospecting is used to identify anomalous underground bodies, which are typically identified by inversion results. In recent years, machine learning has been applied to many geophysics studies, including geophysical data processing and fault… read more here.
Keywords: net recognition; geophysical inversion; application net; inversion results ... See more keywords
Physically Driven Self-Supervised Learning and its Applications in Geophysical Inversion
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DOI: 10.1109/tgrs.2024.3368016
Abstract: Sparse coding (SC) has been proven effective in various geological tasks, such as seismic time–frequency (TF) analysis and seismic reflection inversion. Nevertheless, it inevitably has several drawbacks, for example, low computational efficiency and difficulty in… read more here.
Keywords: driven self; self supervised; supervised learning; geophysical inversion ... See more keywords
Quantifying Model Misrepresentation in Geophysical Inversion for Critical Mineral Exploration
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DOI: 10.1109/tgrs.2025.3541538
Abstract: Geophysical inversion often leans on simplified geological models due to a lack of detailed geological information in greenfield critical mineral exploration. While the actual orebodies are more complex in geometry, the simplified model representation can… read more here.
Keywords: geophysical inversion; misrepresentation; model; geometry ... See more keywords